+++ /dev/null
-/*
- Stockfish, a UCI chess playing engine derived from Glaurung 2.1
- Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
-
- Stockfish is free software: you can redistribute it and/or modify
- it under the terms of the GNU General Public License as published by
- the Free Software Foundation, either version 3 of the License, or
- (at your option) any later version.
-
- Stockfish is distributed in the hope that it will be useful,
- but WITHOUT ANY WARRANTY; without even the implied warranty of
- MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- GNU General Public License for more details.
-
- You should have received a copy of the GNU General Public License
- along with this program. If not, see <http://www.gnu.org/licenses/>.
-*/
-
-// Code for calculating NNUE evaluation function
-
-#include <iostream>
-#include <set>
-
-#include "../evaluate.h"
-#include "../position.h"
-#include "../misc.h"
-#include "../uci.h"
-
-#include "evaluate_nnue.h"
-
-namespace Eval::NNUE {
-
- uint32_t kpp_board_index[PIECE_NB][COLOR_NB] = {
- // convention: W - us, B - them
- // viewed from other side, W and B are reversed
- { PS_NONE, PS_NONE },
- { PS_W_PAWN, PS_B_PAWN },
- { PS_W_KNIGHT, PS_B_KNIGHT },
- { PS_W_BISHOP, PS_B_BISHOP },
- { PS_W_ROOK, PS_B_ROOK },
- { PS_W_QUEEN, PS_B_QUEEN },
- { PS_W_KING, PS_B_KING },
- { PS_NONE, PS_NONE },
- { PS_NONE, PS_NONE },
- { PS_B_PAWN, PS_W_PAWN },
- { PS_B_KNIGHT, PS_W_KNIGHT },
- { PS_B_BISHOP, PS_W_BISHOP },
- { PS_B_ROOK, PS_W_ROOK },
- { PS_B_QUEEN, PS_W_QUEEN },
- { PS_B_KING, PS_W_KING },
- { PS_NONE, PS_NONE }
- };
-
- // Input feature converter
- LargePagePtr<FeatureTransformer> feature_transformer;
-
- // Evaluation function
- AlignedPtr<Network> network;
-
- // Evaluation function file name
- std::string fileName;
-
- namespace Detail {
-
- // Initialize the evaluation function parameters
- template <typename T>
- void Initialize(AlignedPtr<T>& pointer) {
-
- pointer.reset(reinterpret_cast<T*>(std_aligned_alloc(alignof(T), sizeof(T))));
- std::memset(pointer.get(), 0, sizeof(T));
- }
-
- template <typename T>
- void Initialize(LargePagePtr<T>& pointer) {
-
- static_assert(alignof(T) <= 4096, "aligned_large_pages_alloc() may fail for such a big alignment requirement of T");
- pointer.reset(reinterpret_cast<T*>(aligned_large_pages_alloc(sizeof(T))));
- std::memset(pointer.get(), 0, sizeof(T));
- }
-
- // Read evaluation function parameters
- template <typename T>
- bool ReadParameters(std::istream& stream, T& reference) {
-
- std::uint32_t header;
- header = read_little_endian<std::uint32_t>(stream);
- if (!stream || header != T::GetHashValue()) return false;
- return reference.ReadParameters(stream);
- }
-
- } // namespace Detail
-
- // Initialize the evaluation function parameters
- void Initialize() {
-
- Detail::Initialize(feature_transformer);
- Detail::Initialize(network);
- }
-
- // Read network header
- bool ReadHeader(std::istream& stream, std::uint32_t* hash_value, std::string* architecture)
- {
- std::uint32_t version, size;
-
- version = read_little_endian<std::uint32_t>(stream);
- *hash_value = read_little_endian<std::uint32_t>(stream);
- size = read_little_endian<std::uint32_t>(stream);
- if (!stream || version != kVersion) return false;
- architecture->resize(size);
- stream.read(&(*architecture)[0], size);
- return !stream.fail();
- }
-
- // Read network parameters
- bool ReadParameters(std::istream& stream) {
-
- std::uint32_t hash_value;
- std::string architecture;
- if (!ReadHeader(stream, &hash_value, &architecture)) return false;
- if (hash_value != kHashValue) return false;
- if (!Detail::ReadParameters(stream, *feature_transformer)) return false;
- if (!Detail::ReadParameters(stream, *network)) return false;
- return stream && stream.peek() == std::ios::traits_type::eof();
- }
-
- // Evaluation function. Perform differential calculation.
- Value evaluate(const Position& pos) {
-
- alignas(kCacheLineSize) TransformedFeatureType
- transformed_features[FeatureTransformer::kBufferSize];
- feature_transformer->Transform(pos, transformed_features);
- alignas(kCacheLineSize) char buffer[Network::kBufferSize];
- const auto output = network->Propagate(transformed_features, buffer);
-
- return static_cast<Value>(output[0] / FV_SCALE);
- }
-
- // Load eval, from a file stream or a memory stream
- bool load_eval(std::string streamName, std::istream& stream) {
-
- Initialize();
- fileName = streamName;
- return ReadParameters(stream);
- }
-
-} // namespace Eval::NNUE